Sentiment analysis : mining opinions, sentiments, and emotions / Bing Liu, University of Illinois at Chicago.

Includes bibliographical references (pages 327-361) and index.

"Sentiment analysis is the computational study of people's opinions, sentiments, emotions, and attitudes. This fascinating problem is increasingly important in business and society. It offers numerous research challenges but promises insight useful to anyone interested in opinion analysis and social media analysis. This book gives a comprehensive introduction to the topic from a primarily natural-language-processing point of view to help readers understand the underlying structure of the problem and the language constructs that are commonly used to express opinions and sentiments. It covers all core areas of sentiment analysis, includes many emerging themes, such as debate analysis, intention mining, and fake-opinion detection, and presents computational methods to analyze and summarize opinions. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences"-- Provided by publisher.

"Opinion and sentiment and their related concepts such as evaluation, appraisal, attitude, affect, emotion and mood are about our subjective feelings and beliefs. They are central to the human psychology and are key influencers of our behaviors. Our beliefs and perceptions of reality, as well as the choices we make, are to a considerable degree conditioned upon how others see and perceive the world. Due to this reason, our views about the world are very much influenced by those of others, and whenever we need to make a decision we often seek out others' opinions. This is not only true for individuals but also true for organizations. From an application point of view, we naturally want to mine people's opinions and feelings toward any subject matter of interest, which is the task of sentiment analysis. More precisely, sentiment analysis, which is also called opinion mining, is a field of study that aims to extract opinions and sentiments from natural language text using computational methods"-- Provided by publisher.

Machine generated contents note: 1. Introduction; 2. The problem of sentiment analysis; 3. Document sentiment classification; 4. Sentence subjectivity and sentiment classification; 5. Aspect sentiment classification; 6. Aspect and entity extraction; 7. Sentiment lexicon generation; 8. Analysis of comparative opinions; 9. Opinion summarization and search; 10. Analysis of debates and comments; 11. Mining intentions; 12. Detecting fake or deceptive opinions; 13. Quality of reviews.